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首页> 外文会议>World Multiconference on Systemics, Cybernetics and Informatics and 5th International Conference on Information Systems Analysis and Synthesis Vol.5: Computer Science and Engineering, Jul 31-Aug 4, 1999, Orlando, Florida >Interactive Data Mining for Natural Product Drug Discovery
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Interactive Data Mining for Natural Product Drug Discovery

机译：用于天然药物发现的交互式数据挖掘

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摘要

Pharmaceutical research is a high technology, high cost operation, which has the potential to provide new and improved therapies for many disease conditions. One approach for new drug discovery is the high throughput biological screening of natural products (such as plant or microbial samples) in the search for bio-active molecular lead molecules with potential medicinal values. In order to make better and informed decisions at various stages of the drug discovery process, there is a pressing need to discover and extract critical, relevant and useful information or knowledge from the voluminous scientific data accumulated in databases. In this paper we share our experience in applying data mining techniques to facilitate data exploration and analysis of a drug screening database in a natural product drug discovery environment The paper will discuss the challenges of data analysis in such a domain, and the main phases in the knowledge discovery process. The application illustrates the importance of using appropriate domain knowledge and maintaining interactivity during the discovery process. A cognitive-driven framework for data mining is presented which highlights the synergy of data mining techniques such as visualisation and rule discovery, during intermediate phases of the analysis process.
机译：药物研究是一项高科技，高成本的运作，有潜力为许多疾病提供新的和改进的疗法。新药发现的一种方法是对天然产物（例如植物或微生物样品）进行高通量生物筛选，以寻找具有潜在医学价值的生物活性分子铅分子。为了在药物发现过程的各个阶段做出更好，更明智的决策，迫切需要从数据库中积累的大量科学数据中发现并提取关键，相关和有用的信息或知识。在本文中，我们分享了在自然产品药物发现环境中应用数据挖掘技术促进药物筛选数据库的数据探索和分析方面的经验。本文将讨论在这一领域中数据分析的挑战，以及该领域的主要阶段。知识发现过程。该应用程序说明了在发现过程中使用适当的领域知识并保持交互性的重要性。提出了一种认知驱动的数据挖掘框架，该框架突出了在分析过程的中间阶段，诸如可视化和规则发现之类的数据挖掘技术的协同作用。

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